Test the accuracy of cardinality estimation via end-to-end tests against real data in mongod collections. The tests should be implemented via the golden-test framework developed by SERVER-67415.

This task should consider how to generate the dataset(s) used for the test. So far the most likely approach is to use the Python framework developed by WRITING-11332 to pre-generate datasets, and commit to master only the JS tests with their dataset(s).

In more detail:

• generate a variety of datasets similar to the ones in the hist-ce tests,
• evaluate and decide whether to pre-record the generated datasets, or generate them dynamically,
• evaluate the cumulative accuracy results, and compare them to the hist-ce results,
• record expected results using the golden test framework,
• the testing framework should compute a baseline for each test either via running a separate count query, or explain("executionStats") and pick the actual counts from there.